This course gives an introduction into empirical methods used in modern industrial organization. We will discuss typical issues and solutions that come up in the estimation of production functions, demand systems, and models of industry competition. We will examine some applications of the above methods such as merger simulations and prediction of welfare effects of market interventions. There is no textbook in this course; we will discuss papers on the reading list spending approximately one class per paper.

Learning Outcomes:

Familiarity with econometric tools used to estimate models of industry competition.

Analytic skills that can be used to predict the impact of outside interventions on consumer welfare, profits and other market outcomes.

Programming skills useful in modeling industry competition.

Ability to follow and critically evaluate current research literature in the area of empirical industrial organization.

Assessment:

There will be two home assignments, each contributing 30% to the final grade. Each student will present a paper (20%) and submit a referee report (20%).

Prerequisites:

Students must have completed at least the first-year MA sequence of microeconomics and econometrics. Prior knowledge of advanced econometrics (the method of maximum likelihood and the generalized method of moments) and programming experience are a plus (for those who are new to programming in Stata and Matlab we will have an overview session).